The Trials and Tribulations of Machine Learning

December 20 2017

Last night I presented my final project for my Applied Machine Learning class. I tried to predict whether patients would or wouldn’t show up for medical appointments. I tried to use age, alcoholism, hypertension, and a variety of other features in my model.

In all honesty, the project didn’t go as well as I hoped. My model wasn’t really able to perform better than human intuition. Maybe with a more robust dataset, deeper models, or more instances, we might be able to solve the problem, but I wasn’t able to at least.

I am glad this happened though. It taught me that human beings and the world are full of complexities and randomness. And that sometimes you can’t just throw machine learning at a complex problem and expect that to magically solve it.

Through this process, I learned the obstacles of big end to end machine learning projects and how to communicate those projects to my peers.

To quote Frederick Douglass “Without a struggle, there can be no progress.”